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kategorie
2 032
podkategorie
23 060
pojęcia
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pojęcia

Model-Based Offline RL

Offline reinforcement learning approach that learns a dynamic model of the environment to generate synthetic data and improve the policy without real interaction.

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Imagination Rollouts

Simulated trajectories generated using the learned model of the environment to explore potential future states without real interaction with the environment.

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Conservative Policy Optimization

Algorithm that explicitly penalizes policies that significantly deviate from the training data behavior to avoid extrapolation errors.

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Uncertainty Quantification

Technique to estimate the uncertainty of the dynamic model in out-of-distribution regions to guide exploration and avoid catastrophic errors.

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Ensemble Models

Collection of multiple dynamic models trained with different initializations to estimate epistemic uncertainty through prediction variance.

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Trajectory Transformers

Transformer architecture that models trajectories as sequences of states, actions, and rewards to predict future transitions in offline learning.

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Offline-to-Online Transfer

Process of transferring a policy learned offline to an online environment for refinement and continuous adaptation with real interaction.

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Model Ensembling

Technique using multiple dynamic models to capture different hypotheses about state transition and improve prediction robustness.

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Advantage Weighted Regression

Offline method that weights actions in training data according to their estimated advantage to improve policy beyond simple cloning.

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Out-of-Distribution Detection

Mechanism to identify when states generated by the model significantly deviate from the original training data distribution.

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